Airline maintenance task scheduling takes place in a disruptive environment. The stochastic arrival of corrective maintenance tasks and changes in both fleet and resource availability require schedules to be continuously adjusted. An optimal schedule ensures that all tasks are executed before their due date in both an efficient (at minimum use of ground-time) and a stable (limited number of schedule changes) manner. This paper is the first study to address disruption management for the hangar maintenance task scheduling problem, proposing a practical and efficient modeling framework. The framework comprises a mixed integer linear programming model for airline maintenance task rescheduling in a disruptive environment, in which task scheduling is constrained by the availability of resources. The model's capabilities include creating and adjusting maintenance schedules continuously and dynamically reacting to new information when this becomes available. The modeling framework was tested in a case study provided by a large airline, and its performance was compared to the current practice of the airline. The results show that the proposed approach produces more efficient and stable results. A 3% ground time decrease was achieved, while the number of schedule changes in the last days before operations was decreased by more than half.